Authors: Dr. Sadaf Khan, Kajal Yadav, Kartikey Sirohiya, Bharat Lal Napit
Abstract: Artificial Intelligence (AI) has emerged as a transformative technology in the banking and financial services sector, revolutionizing the way financial institutions operate and interact with customers. AI-driven technologies such as machine learning, natural language processing, predictive analytics, and robotic process automation are enhancing operational efficiency, improving customer experiences, strengthening fraud detection mechanisms, and supporting data-driven financial decision-making. As banks increasingly adopt digital transformation strategies, AI plays a vital role in delivering personalized financial services, automating routine processes, and managing financial risks more effectively. This study aims to examine the impact of Artificial Intelligence on banking and financial services by exploring its opportunities, challenges, and future directions. The research adopts a descriptive research design and utilizes primary data collected through a structured questionnaire administered to 100 respondents, including banking professionals and customers. Convenience sampling has been employed, while the collected data are analyzed using descriptive statistical techniques through MS Excel and SPSS. The expected findings indicate that AI significantly improves service quality, enhances customer satisfaction, accelerates decision-making, and reduces operational costs and fraudulent activities. However, challenges such as data privacy concerns, cybersecurity risks, algorithmic bias, regulatory compliance, and the need for skilled professionals continue to influence AI implementation. The study concludes that Artificial Intelligence should be viewed as a strategic enabler that complements human expertise rather than replacing it entirely. By integrating AI responsibly and ethically, financial institutions can achieve sustainable growth, improve customer trust, and maintain competitiveness in the rapidly evolving digital financial ecosystem.
DOI: http://doi.org/10.5281/zenodo.21808067
